ABSTRACT Evaluation of prostate cancer prognosis after surgery is increasingly relying upon genomic analyses of tumor DNA. We assessed the ability of the biomarker panel Genomic Evaluators of Metastatic Prostate Cancer (GEMCaP) to predict biochemical recurrence in 33 European American and 28 African American prostate cancer cases using genome-wide copy number data from a previous study. "Biomarker positive" was defined as ≥20% of the 38 constituent copy number gain/ loss GEMCaP loci affected in a given tumor; based on this threshold, the frequency of a positive biomarker was significantly lower in African Americans (n=2; 7%) than European Americans (n=11; 33%; p=0.013). GEMCaP positivity was associated with risk of recurrence (HR=5.92; 95%CI=2.32-15.11; p=3*10-4) in the full sample and among European Americans (HR=3.45; 95%CI=1.13-10.51; p=0.032) but was not estimable in African Americans due to the low rate of GEMCaP positivity. Overall, the GEMCaP recurrence positive predictive value (PPV) was 85%; in African Americans, PPV was 100%. When we expanded the definition of loss to include copy-neutral loss of heterozygosity (i.e. loss of one allele with concomitant duplication of the other), recurrence PPV was 83% for European American subjects. Under this definition, five African American subjects had a positive GEMCaP test value; four went on to develop biochemical recurrence (PPV=80%). Our results suggest that the GEMCaP biomarker set could be an effective predictor for both European American and African American men diagnosed with localized prostate cancer who may benefit from immediate aggressive therapy after radical prostatectomy.

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High-density single nucleotide polymorphism (SNP) mapping arrays have identified chromosomal features whose importance to cancer predisposition and progression is not yet clearly defined. Of interest is that the genomes of normal somatic cells (reflecting the combined parental germ-line contributions) often contain long homozygous stretches. These chromosomal segments may be explained by the common ancestry of the individual's parents and thus may also be called autozygous. Several studies link consanguinity to higher rates of cancer, suggesting that autozygosity (a genomic consequence of consanguinity) may be a factor in cancer predisposition. SNP array analysis has also identified chromosomal regions of somatic uniparental disomy (UPD) in cancer genomes. These are chromosomal segments characterized by loss of heterozygosity (LOH) and a normal copy number (two) but which are not autozygous in the germ-line or normal somatic cell genome. In this review, we will also discuss a model [cancer gene activity model (CGAM)] that may explain how autozygosity influences cancer predisposition. CGAM can also explain how the occurrence of certain chromosomal aberrations (copy number gain, LOH, and somatic UPDs) during carcinogenesis may be dependent on the germ-line genotypes of important cancer-related genes (oncogenes and tumor suppressors) found in those chromosomal regions.

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The authors previously developed and validated the Cancer of the Prostate Risk Assessment (CAPRA) score to predict prostate cancer recurrence based on pretreatment clinical data. They aimed to develop a similar postsurgical score with improved accuracy via incorporation of pathologic data.
A total of 3837 prostatectomy patients in the Cancer of the Prostate Strategic Urologic Research Endeavor (CaPSURE™) national disease registry were analyzed. Cox regression was used to determine the predictive power of preoperative prostate-specific antigen (PSA), pathologic Gleason score (pGS), surgical margins (SM), extracapsular extension (ECE), seminal vesicle invasion (SVI), and lymph node invasion (LNI). Points were assigned based on the relative weights of these variables in predicting recurrence. The new postsurgical score (CAPRA-S) was tested and compared with a commonly cited nomogram with proportional hazards analysis, concordance (c) index, calibration plots, and decision-curve analysis.
Recurrence appeared in 16.8% of the men; actuarial progression-free probability at 5 years was 78.0%. The CAPRA-S was determined by adding up to 3 points for PSA, up to 3 points for pGS, 1 point each for ECE and LNI, and 2 points each for SM and SVI. The hazard ratio for each point increase in CAPRA-S score was 1.54 (95% confidence interval, 1.49-1.59), indicating a 2.4-fold increase in risk for each 2-point increase in score. The CAPRA-S c-index was 0.77, substantially higher than 0.66 for the pretreatment CAPRA score and comparable to 0.76 for the nomogram. The CAPRA-S score performed better in both calibration and decision curve analyses.
The CAPRA-S offers good discriminatory accuracy, calibration, and ease of calculation for clinical and research settings.

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